Perform fast interactive analytics against different data sources using the Presto high-performance, distributed SQL query engine. With this practical guide, you�?�¢??ll learn how to conduct analytics on data where it lives, whether it�?�¢??s Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production engineers will learn how to manage, use, and even develop with Presto. Initially developed by Facebook, open source Presto is now used by Netflix, Airbnb, LinkedIn, Twitter, Uber, and many other companies. Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Presto query can combine data from multiple sources to allow for analytics across your entire organization. Get started: Explore Presto�?�¢??s use cases and learn about tools that will help you connect to Presto and query data Go deeper: Learn Presto�?�¢??s internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and more Put Presto in production: Secure Presto, monitor workloads, tune queries, and connect more applications; learn how other organizations apply Presto

Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.

This book constitutes the proceedings of the 7th International Conference on Future Data and Security Engineering, FDSE 2020, held in Quy Nhon, Vietnam, in November 2020.* The 29 full papers and 8 short were carefully reviewed and selected from 161 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; data analytics and healthcare systems; machine learning-based big data processing; emerging data management systems and applications; and short papers: security and data engineering. * The conference was held virtually due to the COVID-19 pandemic.

This book constitutes the proceedings of the 18th International Conference on Web Information Systems and Applications, WISA 2021, held in Kaifeng, China, in September 2021. The 49 full papers and 18 short papers presented were carefully reviewed and selected from 206 submissions. The papers are grouped in topical sections on world wide web, query processing and algorithm, natural language processing, machine learning, data mining, data privacy and security.